Fix test

Signed-off-by: zethson <[email protected]>

src/scportrait/data/_datasets.py

@@ -8,7 +8,7 @@ def dataset_1() -> Path:
     """Download and extract the example dataset 1 images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "example_1_images"
@@ -25,7 +25,7 @@ def dataset_2() -> Path:
     """Download and extract the example dataset 2 images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "example_2_images"
@@ -42,7 +42,7 @@ def dataset_3() -> Path:
     """Download and extract the example dataset 3 images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "example_3_images"
@@ -59,7 +59,7 @@ def dataset_4() -> Path:
     """Download and extract the example dataset 4 images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "example_4_images"
@@ -76,7 +76,7 @@ def dataset_5() -> Path:
     """Download and extract the example dataset 5 images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "example_5_images"
@@ -93,7 +93,7 @@ def dataset_6() -> Path:
     """Download and extract the example dataset 6 images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "example_6_images"
@@ -110,7 +110,7 @@ def dataset_stitching_example() -> Path:
     """Download and extract the example dataset for stitching images.
 
     Returns:
-        Path: Path to the downloaded and extracted images.
+        Path to the downloaded and extracted images.
     """
     data_dir = Path(get_data_dir())
     save_path = data_dir / "stitching_example"

src/scportrait/pipeline/_utils/segmentation.py

@@ -271,7 +271,7 @@ def _return_edge_labels_2d(input_map: NDArray) -> list[int]:
         .union(set(last_column.flatten()))
     )
 
-    full_union = {np.uint64(i) for i in full_union}
+    full_union = set([np.uint64(i) for i in full_union])  # noqa: C403
     full_union.discard(0)
 
     return list(full_union)

src/scportrait/pipeline/_utils/spatialdata_helper.py

@@ -37,7 +37,7 @@ def check_memory(item: xarray.DataArray) -> bool:
 
 
 def generate_region_annotation_lookuptable(sdata: SpatialData) -> dict[str, list[tuple[str, TableModel]]]:
-    """Generate lookup table for region annotations.
+    """Generate a lookup table for the region annotation tables contained in a SpatialData object ordered according to the region they annotate.
 
     Args:
         sdata: SpatialData object to process
@@ -75,7 +75,7 @@ def remap_region_annotation_table(table: TableModel, region_name: str) -> TableM
     table.obs["region"] = table.obs["region"].astype("category")
 
     if "spatialdata_attrs" in table.uns:
-        del table.uns["spatialdata_attrs"]
+        del table.uns["spatialdata_attrs"]  # remove the spatialdata attributes so that the table can be re-written
 
     return TableModel.parse(table, region_key="region", region=region_name, instance_key="cell_id")
 

src/scportrait/tools/ml/utils.py

@@ -38,7 +38,7 @@ def combine_datasets_balanced(
     elements = [len(el) for el in list_of_datasets]
     rows = np.arange(len(list_of_datasets))
 
-    # create dataset fraction array
+    # create dataset fraction array of len(list_of_datasets)
     mat = csr_matrix((elements, (rows, class_labels))).toarray()
     cells_per_class = np.sum(mat, axis=0)
     normalized = mat / cells_per_class
@@ -168,9 +168,7 @@ def split_dataset_fractions(
         else:
             residual_size = len(dataset) - train_size - test_size - val_size
             if residual_size < 0:
-                raise ValueError(
-                    f"Dataset with length {len(dataset)} is too small to be split into " f"requested sizes"
-                )
+                raise ValueError(f"Dataset with length {len(dataset)} is too small to be split into requested sizes")
 
             if seed is not None:
                 gen = torch.Generator()